Publication Type:

Journal Article

Source:

Journal of Computer Science, Volume 9, Number 6, p.757-762 (2013)

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-84880142972&partnerID=40&md5=dc1fbe98ea752dd743f69354840c41e8

Abstract:

Video surveillance is an important aspect in today's world, where a particular scene of area requires monitoring to avoid terrorist attacks and unauthorized entries. Vehicle recognition is an important area in object tracking and recognition. Objects may be of rigid or non-rigid in nature with varying velocity and have different features. Important features like shape, logo, color and texture are complex in nature. Hence there is a need of better algorithm for detecting and identifying the objects like car. A new method is proposed for recognizing the cars present in the video. At first the features like shape is extracted using moments, logo using the Scale Invariant Feature Transform (SIFT) and the RGB color values of the car body. Using these features the recognition is carried out to classify the type of car. Recognition of cars has range of application like, military surveillance, traffic management, autonomous navigation system, auto parking. © 2013 Science Publications.

Notes:

cited By (since 1996)0

Cite this Research Publication

Ga Murugesan, Dr. Shriram K Vasudevan, Ramachandran, Sc, Vasudevan, Sd, and Arumugam, Be, “Vehicle identification using fuzzy adaline neural network”, Journal of Computer Science, vol. 9, pp. 757-762, 2013.

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